The era of artificial neural network (ANN) began with a simplified application in many fields
and remarkable success in pattern recognition (PR) even in manufacturing industries …

With the transition of facial expression recognition (FER) from laboratory-controlled to
challenging in-the-wild conditions and the recent success of deep learning techniques in …

Facial emotion recognition (FER) is an important topic in the fields of computer vision and
artificial intelligence owing to its significant academic and commercial potential. Although …

Automated Facial Expression Recognition (FER) in the wild using deep neural networks is
still challenging due to intra-class variations and inter-class similarities in facial images …

Facial emotion recognition (FER) is an emerging and significant research area in the pattern
recognition domain. In daily life, the role of non-verbal communication is significant, and in …

Current artificial intelligence systems for determining a person's emotions rely heavily on lip
and mouth movement and other facial features such as eyebrows, eyes, and the forehead …

We present an approach that combines automatic features learned by convolutional neural
networks (CNN) and handcrafted features computed by the bag-of-visual-words (BOVW) …

Facial expression recognition (FER) is an emerging and multifaceted research topic.
Applications of FER in healthcare, security, safe driving, and so forth have contributed to the …

An image is worth a thousand words; hence, a face image illustrates extensive details about
the specification, gender, age, and emotional states of mind. Facial expressions play an …

Many researchers have been seeking robust emotion recognition system for already last two
decades. It would advance computer systems to a new level of interaction, providing much …